Journal
ENERGIES
Volume 8, Issue 11, Pages 13162-13193Publisher
MDPI
DOI: 10.3390/en81112361
Keywords
energy; time series; forecasting; data mining
Categories
Funding
- Spanish Ministry of Economy and Competitiveness
- Junta de Andalucia
- Pablo de Olavide University [TIN2014-55894-C2-R, P12-TIC-1728, APPB813097]
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Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques it includes and the successful results obtained in many application fields, make this family of approaches powerful and widely used. In particular, this work explores the application of these techniques to time series forecasting. Although classical statistical-based methods provides reasonably good results, the result of the application of data mining outperforms those of classical ones. Hence, this work faces two main challenges: (i) to provide a compact mathematical formulation of the mainly used techniques; (ii) to review the latest works of time series forecasting and, as case study, those related to electricity price and demand markets.
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